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Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions
We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution....
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648298/ https://www.ncbi.nlm.nih.gov/pubmed/29049392 http://dx.doi.org/10.1371/journal.pone.0186566 |